Macroeconomic Factors and Equity Premium Predictability

Neely et al. (2014) have recently demonstrated how to efficiently combine information from a set of popular technical indicators together with the standard Goyal andWelch (2008) predictor variables widely used in the equity premium forecasting literature to improve outof- sample forecasts of the equity premium using a small number of principal components. We show that forecasts of the equity premium can be further improved by, first, incorporating broader macroeconomic data into the information set, second, improving the selection of the most relevant factors and combining the most relevant factors by means of a forecast combination regression, and third, imposing theoretically motivated positivity constraints on the forecasts of the equity premium. Applying standard out-of-sample forecast evaluation tests, we find that in particular our proposed forecast combination approach, which combines forecasts of the most relevant Neely et al. (2014) and macroeconomic factors and further imposes positivity constraints on the equity premium forecasts, generates statistically significant and economically sizable improvements over the best performing model of Neely et al. (2014). Out-of-sample R2 values can be as high as 1.75%, with (annualised) gains in certainty equivalent returns of up to 3.35%, relative to the ALL factors forecasts of Neely et al. (2014).